By Rene-Pascal Fischer, scientist and software architect, Fraunhofer IESE
In the rapidly evolving landscape of pharmaceutical manufacturing, a revolutionary wave is breaking on the shores of innovation — Pharma 4.0, a term coined by the International Society for Pharmaceutical Engineering (ISPE) in 2017 with the goal to utilize the ideas of Industry 4.0 for the specifics of the pharmaceutical domain.
At the heart of this transformation lies the idea of complete digitalization and thus interoperability. Being a derivative of Industry 4.0, the basic concepts have already been introduced and just need to be adapted to the unique field that is the pharmaceutical domain.
Digitalization is no longer a buzzword confined to other industries; it is steadily permeating into pharmaceutical manufacturing. New cutting-edge technologies such as AI, the industrial Internet of Things (IIoT), and digital twins (DTs) redefine manufacturing as part of the fourth industrial revolution.
However, even with many enthusiastic discussions surrounding the potential of Pharma 4.0 and the integration of DTs, it’s important to acknowledge that we are standing at the beginning of a transformative journey that demands our full attention.
Housekeeping Required: Laying The Digitalization Foundation
The absence of a holistic digitalization process, and often digitalization itself,1 paints a picture of an industry still operating in silos, with each company navigating its own unique path toward the future. While some companies are investing in or even developing their own technologies to combat this, others are bound to traditional, paper-based manufacturing processes with no sign of change. This disjointed approach not only impedes the efficient use and rollout of digital applications but also raises new challenges in terms of compliance, communication, and quality assurance, especially in larger supply chains.2
In today’s pharmaceutical manufacturing environment, physical notes on paper remain an important aspect of quality assurance and show the existing gap between the industry’s current state and the envisioned future.3 Despite advancements, many companies still rely on paper-based records for quality assurance, a reactive strategy that falls short of the proactive, real-time monitoring and manufacturing adjustments promised by DTs.
As the pharmaceutical sector confronts these challenges, the need for change becomes more and more important. Breaking the silo structure, establishing industry-wide standards for digitalization, and embracing a fully integrated digital landscape are not only visions — they are essential steps toward a more adaptable, interoperable, and efficient future for the pharmaceutical domain.
Unpacking The Current State Of Digital Twin Technology
To achieve this future, existing concepts of Industry 4.0 and other digitalization efforts can be adjusted to fit the unique landscape. The concept of DTs is one highly important aspect that offers a seamless bridge between the present challenges and the vision of Pharma 4.0.
DTs, in essence, are virtual representations of physical (and conceptual) assets, processes, or systems. They extend beyond mere static depictions by adding a dynamic flow of information to the digital space but also a way to control the assets and their respective aspects.4 Leveraging data from sensors, IIoT devices, and other sources, DTs provide a comprehensive view of a facility and its individual components while simultaneously allowing for a holistic control strategy. This holistic perspective empowers decision makers with real-time insights, enabling them to optimize operational efficiency.
A special advantage of DTs is their role as a connective tissue within the facility and abroad. They overcome traditional barriers and allow for improved usage of all the data available, while using a standardized form that allows for other systems to plug into the ecosystem with little to no configuration needed. In essence, DTs create a shared language, allowing every actor, from machinery to personnel, to understand and contribute to the ongoing processes and development.
Germany, at the forefront of the fourth industrial revolution, is pioneering standards through initiatives like the “Plattform Industrie 4.0” and Industrial Digital Twin Association. Together with multiple manufacturing companies, they proposed the Asset Administration Shell (AAS) as a unified language for DTs, ensuring compatibility and facilitating seamless integration across various domains, as well as within and between facilities. Open-source initiatives, like these, help with the adoption of a unified language that has no proprietary elements, which might be an obstacle that companies avoid.
A standardized DT, such as the AAS, in combination with open protocols, such as MQTT or OPC UA, offers a road map for asset manufacturers, ensuring they can seamlessly integrate their products into existing or new infrastructures. This includes the simulation of new production lines and preemptively improving the efficiency before building the line itself.5 Importantly, this standardized approach also ensures the upgradeability of legacy systems, allowing them to be retrofitted with the necessary technologies. This adaptability safeguards the value of significant investments, ensuring that even expensive assets can be revitalized with the addition of a few sensors or adapters to enable communication with other systems.
However, the impact of DTs extends beyond equipment to the realms of predictive analytics, simulation, and quality assurance. In a future where guesswork is replaced by data-driven insights, software services can predict or simulate potential failures in the manufacturing process. With this information, decisions to abort the current process and restart from scratch rather than waiting for its completion and subsequent quality checks can be supported or even autonomously made by the system itself.6
This also includes logistics, a critical element in the pharmaceutical domain. The digital representations of products capture information about their conditions during transport.7 In the event of a deviation from optimal conditions, such as temperature differences, scheduling systems can act immediately and reroute or reorder packages, ensuring product – and, thus, patient – safety and minimizing disruptions.
As we navigate the complex landscape of pharmaceutical manufacturing, DTs emerge not only as a technological solution but as a catalyst for a paradigm shift. They pave the way for a future where communication is seamless, decision-making is data-driven, and the pharmaceutical industry operates on the forefront of innovation, propelled by the transformative power of digitalization.
Three Challenge Areas For Digital Twin Adoption: Regulatory, Data Integrity, And Standards
The integration of DTs in pharmaceutical manufacturing, while promising, faces several hurdles. Companies, though aware of the benefits, remain hesitant, requiring a decisive push toward adoption. Drawing lessons from other industries, particularly automotive, is beneficial, but a tailored approach for pharmaceutical intricacies is crucial.
Regulatory aspects, although not inherently relevant to the digitalization process itself, pose a significant hurdle. The pharmaceutical industry operates under stringent regulations, and any new technological integration must align with existing regulatory frameworks. Overcoming these regulatory challenges necessitates collaboration between industry stakeholders and regulatory bodies to ensure a harmonized approach that fosters innovation while maintaining compliance.
Data integrity emerges as a critical concern in the realm of DTs.8 While DTs inherently offer a robust electronic batch record, the use of advanced technologies such as artificial intelligence (AI), machine learning (ML), or simulation as part of a DT still faces the issue of understandability and reliability.
The unique nature of GxP standards in the pharmaceutical domain adds another level of complexity. To fully leverage the benefits of DTs, it is imperative to find ways to integrate GxP requirements seamlessly into the existing technological frameworks. Rather than creating a new set of standards, efforts should focus on adapting and extending existing technologies to meet the specific needs of the pharmaceutical industry.
The adoption of DTs is not a distant vision but, rather, it is a present reality, as evidenced by their successful integration in manufacturing across various domains. The lessons from automotive and other industries underscore the immense potential for DTs to revolutionize pharmaceutical production.
Now, the imperative is to seize the low-hanging fruits of this transformative technology, preparing ourselves for a future where digital processes afford a holistic view of manufacturing. This not only encompasses the manufacturing process itself but also addresses the intricate logistical challenges interconnected with it.
Crucially, as we edge closer to personalized therapies on a mass scale, the digitalization of the manufacturing process becomes paramount. Modular approaches, facilitated by DTs, emerge as key enablers, ensuring adaptability and scalability. By embracing the possibilities of DTs today, we lay the foundation for a future where pharmaceutical manufacturing is not just efficient but also agile and responsive to the demands of individualized therapies. The time to act is now to cultivate a landscape where innovation thrives and the vision of Pharma 4.0 becomes a transformative reality.
- Mishra, S., Yadav, S., Singh, N., Dahiya, R., Verma, S., & Tripathi, S. M. (2023). Digitalization in the Pharmaceutical Industry: Prioritization Throughout the Digital Transformation. In Pharmaceutical industry 4.0: Future, Challenges & Application (pp. 1-22). River Publishers.
- Adhikari, A. A., & Scholar, D. (2021). Digitization deployment challenges in pharmaceutical supply chain. International Journal of Innovative Science and Research Technology, 6(6), 134-142.
- Peel, S., Eggbeer, D., & Dorrington, P. (2020). Standardizing the patient-specific medical device design process via a paper-based pro-forma. Journal of Design, Business & Society, 6(2), 233-258.
- Grieves, M., & Vickers, J. (2017). Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Transdisciplinary perspectives on complex systems: New findings and approaches, 85-113.
- Jiang, Y., Yin, S., Li, K., Luo, H., & Kaynak, O. (2021). Industrial applications of digital twins. Philosophical Transactions of the Royal Society A, 379(2207), 20200360.
- Hribernik, K., Cabri, G., Mandreoli, F., & Mentzas, G. (2021). Autonomous, context-aware, adaptive Digital Twins—State of the art and roadmap. Computers in Industry, 133, 103508.
- Agalianos, K., Ponis, S. T., Aretoulaki, E., Plakas, G., & Efthymiou, O. (2020). Discrete event simulation and digital twins: review and challenges for logistics. Procedia Manufacturing, 51, 1636-1641.
- Alosert, H., Savery, J., Rheaume, J., Cheeks, M., Turner, R., Spencer, C., ... & Goldrick, S. (2022). Data integrity within the biopharmaceutical sector in the era of Industry 4.0. Biotechnology Journal, 17(6), 2100609.
About the Author:
Rene-Pascal Fischer is a scientist and software architect at Fraunhofer IESE focusing on the topic of Industry 4.0 and its adoption in the pharmaceutical domain. Having started his Ph.D. on the topic of validation and certification of processes using digital twins, he is an advocate of holistic digitalization and the connected enablement of a digital control flow. He is actively contributing to open-source software and multiple research projects for both industry and Pharma 4.0 as well as the CoP Pharma 4.0 of the ISPE. Reach him at firstname.lastname@example.org.